graphlove.lua

Small and simple graphing library for Love2D in a single lua file.

The simplicity comes from eschewing antialiasing and infinite precision. Graphlove doesn't graph a function itself, instead it takes an array of points and maps them onto the screen.

Usage

It's as easy as the following:

• Drop graphlove.lua into your project and require it:

  local graphlove = require("graphlove")

• Create a new graph:

  local graph = graphlove.new({
     curves = {
        {
           -- {x1, y1, x2, y2, x3 ...}
           points = {1, 1, 2, 2, 3, 3},
           radius = 3,
        }
     }
  })
  
  graphlove.update(graph)

• Draw the graph:

  function love.draw()
     graphlove.draw(graph)
  end

• If you wish to make the graph interactive:

  function love.update(dt)
     -- Use arrow keys and hjkl for controls by default
     graphlove.do_easy_controls(graph, dt)
  end

Documentation

Read the examples section for an introduction. Then just read the code: graphlove.lua. Seriously. It's thoroughly commented and written to be as simple as possible at around 300 lines.

Examples

Interactive examples

The simple example

I highly recommend reading examples/simple/main.lua to see a slightly more complex use case. You can run the included example with:

$ love examples/simple/

And this is what it should look like, two hyperbolae with a random cluster of points around each of them:

That's me scrolling and scaling the graph, which you can also do using hjkl and the arrow keys.

Gradient descent

To run the second example, do:

$ love examples/grad-descent/

It picks a random point on a graph and using 'space' (tapping or holding it down) you can go though a single iteration of gradient descent and see the slope chaning as it reaches a local minimum. Press 'r' to create a new random point. The graph scrolling/scaling controls also apply.

Drawing the logo

To draw the graphs from the first screenshot, I used the following curves:

function gen_points(from, to, int, fn)
   local pts = {}
   for x=from, to, int do
      table.insert(pts, x)
      table.insert(pts, fn(x))
   end
   return pts
end

curves = {
   {
      color = {64/255, 224/225, 208/255, 1},
      points = gen_points(-20, 20, 0.001, function(x)
         return x^3 * 0.6
      end)
   },
   {
      color = {1, 1, 1, 1},
      points = gen_points(-20, 20, 0.01, math.sin)
   },
   {
      color = {1, 215/255, 0, 1},
      points = gen_points(-20, 20, 0.0001, function(x)
         return math.exp(x/2)^math.cos(x) * 2 - 3.5
      end)
   },
   {
      color = {0.8, 120/255, 230/255, 1},
      points = gen_points(-20, 20, 0.0001, function(x)
         local x = math.abs(x)
         return x^math.sin(x^math.cos(x)) + 2.5
      end)
   }
}

Other examples

I use graphlove in one of the examples of my neural network library to show how the model slowly approximates a function: http://github.com/Nikaoto/nn.lua

License (3-clause BSD)

Copyright 2022 Nikoloz Otiashvili.

Redistribution and use in source and binary forms, with or
without modification, are permitted provided that the following
conditions are met:

1. Redistributions of source code must retain the above copyright
   notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above
   copyright notice, this list of conditions and the following
   disclaimer in the documentation and/or other materials
   provided with the distribution.

3. Neither the name of the copyright holder nor the names of its
   contributors may be used to endorse or promote products
   derived from this software without specific prior written
   permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
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LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
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